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ENTITY default mode network

default mode network

PulseAugur coverage of default mode network — every cluster mentioning default mode network across labs, papers, and developer communities, ranked by signal.

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Total · 30d
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6 over 90d
Releases · 30d
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Papers · 30d
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TIER MIX · 90D
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SENTIMENT · 30D

2 day(s) with sentiment data

RECENT · PAGE 1/1 · 6 TOTAL
  1. TOOL · CL_268232 ·

    New Bayesian framework quantifies fMRI connectivity uncertainty

    Researchers have developed a new Bayesian framework to quantify uncertainty in fMRI functional connectivity data. This framework models BOLD dynamics using coupled Ornstein-Uhlenbeck processes and employs Sequential Neu…

  2. COMMENTARY · CL_251130 ·

    AI, Movement, and Mental Clarity: Exploring Cognitive Catalysts

    This cluster of posts explores the intersection of physical movement, mental well-being, and artificial intelligence. The author discusses how exercise can act as a cognitive catalyst, aiding in mental clarity and resil…

  3. COMMENTARY · CL_199516 ·

    AI's broad impact discussed across multiple Mastodon posts · 10 sources tracked

    Multiple posts from Mastodon discuss the multifaceted role of AI, touching on its potential to drive progress in areas like space exploration and conservation, its application in complex coding problems, and its influen…

  4. TOOL · CL_193671 ·

    LLMs Show Brain Alignment During Creative Thinking

    A new study published on arXiv explores the alignment between large language models (LLMs) and the human brain during creative thinking tasks. Researchers used functional magnetic resonance imaging (fMRI) data from part…

  5. RESEARCH · CL_93111 ·

    Krakencoder analysis reveals subtle sex differences in brain connectomes

    A new study published on arXiv analyzes sex-based differences in brain connectomes using the Krakencoder framework. Researchers examined structural and functional connectomes from 702 participants in the Human Connectom…

  6. RESEARCH · CL_38211 ·

    Beta-TCVAE model adapted for nonlinear fMRI data analysis

    Researchers have adapted the $\beta$-TCVAE model to analyze nonlinear fMRI data, aiming to disentangle complex brain signals. This approach moves beyond traditional linear methods by learning meaningful latent represent…